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Truly Typed

A writing app for the AI era

Details

External ID
48125186
Source
HN
Company
—
Product
Truly Typed
Website domain
trulytyped.com
Launched
May 13, 2026
Cohort
—
Upvotes
8
Upvotes percentile
0.4894991922455573
Tags
—
Fetched at
Sept. 7, 2026, 9:26 p.m.
Updated at
Sept. 7, 2026, 9:26 p.m.

Description

Hey HN, this is deepan from trulytyped (https://trulytyped.com). I am building a document writing app which makes it extremely easy to figure out how a document was created.Now that any text can be AI generated, how do you tell if something was actually generated or composed. It is impossible to detect AI after a piece of text has been generated. No amount of watermarking, linguistic checks or vibe checks work consistently. The AI detectors that schools and journals use are easy to bypass.Why do we need to solve this problem - First of all, this is not an anti-AI stance. I have trained machine learning models in healthcare, cybersecurity and privacy space in last 10 years and open sourced some of the stuff (https://github.com/deepanwadhwa). I think, at a very fundamental level, we need to figure out how to differentiate human experience from AI so that we could have continued access to humans. Access through in-person, writing, audio or video. Access through text has already been fractured, our radius of trustworthy written material on the internet has reduced. And I think a similar trajectory will follow for audio, video and in person.So how does truly typed solve this - Each document composed in truly typed carries information such as how much of the content was actually typed, how much was pasted, how many sources were used, how many authors contributed. Each document also carries flags such as verified human, bot detected, unverified. Unverified is for cases where humans are transcribing (basically copying by typing) text looking at another tab or book. The core thesis of the product is that purely human generated thoughts will matter more and more.Since I come from a privacy and security background - Each and every profile and post is private by default. You decide if you want to make it public or not. We also have a pretty tight bot and automation defense - if you are an automation expert - try pointing a script at the app and see if you can get a verified human flag on an article (please reach out to [email protected], if you actually break it). We don't want to use your data for any llm training and we don't want to sell your data to any brokers.Our primary market for now is Academic Journals, News media outlets and Colleges and general folks who just wanna write and share with their audience.We are sort of unique in this offering and competition exists at different layers. Google docs and Microsoft word are both writing apps, but they don't really tell you if the document was actually created by a human or not. We pointed a bunch of our testing scripts at google docs and full articles generated with real keystrokes without google detecting a hair. There are a ton of AI detectors that we have come across which show how much of the text is human or AI but they all are easily bypassable.I am passionate about this problem and would like to hear your feedback, criticism, interest.Cheers,PS: I typed the whole thing myself. On truly typed, you won't have to say this.

Enrichment

Theme
AI text humanizers and detectors
Vertical
Media & entertainment
Function
Content generation
Audience
B2C
AI stance
AI feature
Project type
Commercial product
Normalized one-liner
writing application with ai assistance
Manually corrected
False

Could you build this?

Partial A rich-text editor is easy to vibe code, but capturing keystroke biometrics, typing dynamics, and fine-grained mutation telemetry to prove human authorship requires specialized data science and client-side telemetry.

What it would actually take: The product combines a ProseMirror or Lexical web editor with a low-level event recorder capturing inter-key timings, backspaces, flight times, and paste operations. The hard part is the behavioral biometric model: training a statistical classifier or ML pipeline on keystroke dynamics to reliably distinguish organic human composition from copy-pasted or programmatically typed text while accounting for typing speed variations and network latency.

Discussion

2 comments analyzed.

Competitors

Other products that read as similar to this one — 110 launches clear the similarity bar, closest 8 shown.

Attention rank: #52 of 111 (itself plus its competitors, highest first — normalized so YC and Product Hunt are compared fairly).

Launched 182 days after the earliest competitor.

Other launches for this product

Same idea, different domain

Nobody's really built a content generation tool for Government yet.